From keywords to prompts
Your keyword research isn't obsolete — it's raw material. How to translate keywords into buyer prompts, map them to funnel stages, and track what matters.
Keywords describe demand; prompts describe buyers. "Best CRM" is a keyword with volume. "What's the best CRM for a 10-person team that needs invoicing?" is a prompt an AI assistant actually answers — and names two vendors in. The migration from keywords to prompts is mostly translation plus funnel mapping, not starting over.
The translation method
- Take commercial keywords first. Sort existing research by intent, not volume: comparison and "best" terms translate directly; informational terms need question-framing.
- Expand each into 3–5 full questions. Add the buyer context keywords hide: team size, budget, constraint, incumbent tool. One keyword → a small family of prompts.
- Split branded from unbranded. Branded prompts ("what does Acme do") test recall; unbranded ("best invoice tool for freelancers") test consideration. The money — and the gaps — live in unbranded.
- Map to funnel. Informational (learn), commercial (compare), transactional (buy). Track share of voice per stage; most brands discover they're invisible exactly where buying happens.
What changes in reporting
Positions become percentages, keywords become prompt sets, monthly rank reports become monthly re-queries of the frozen set. Keep keyword volume data for one job only: prioritizing which prompt families to build first.
Related reading
Frequently asked questions
Do I throw away my keyword research?
No — you translate it. Every commercial keyword implies buyer questions ('best CRM' → 'what's the best CRM for a 10-person team that needs invoicing'). Keep the volume data for prioritization; rewrite the queries as full questions for tracking.
How many prompts per topic?
Practitioners running GEO programs target 20–30 prompts per core topic, re-queried monthly. Fewer, buyer-voiced prompts beat hundreds of keyword permutations.
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